Text Standardization and Redundancy Removal in Collaborative Development
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Solution Overview
Problem
Collaborative development environments face challenges due to the presence of redundancies, nonuniform phraseology, tautology, non-standard expressions, and errors in text files, which hinder meaningful collaboration and project progress.
Innovation Solution
A text processing system that extracts text statements, calculates similarity values with a statement database, and replaces redundant or non-standard statements with standardized ones using machine learning algorithms and natural language processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If text processing is performed manually to identify and remove redundancies and nonstandard expressions, then text uniformity can be improved, but productivity is reduced due to the time-consuming nature of manual review
Solution Approach 1:
The patent replaces manual mechanical text review with an automated computer-based system that uses natural language processing and machine learning algorithms to identify redundancies, nonstandard expressions, and inconsistencies, thereby maintaining text uniformity while dramatically improving processing speed and productivity
Solution Approach 2:
The system enables text standardization to occur automatically without requiring manual intervention, with the computer-based platform autonomously analyzing, identifying, and correcting text issues through integrated NLP and ML capabilities, thus eliminating the productivity bottleneck of manual review
2Manufacturing precision
If comprehensive text analysis is performed to identify all types of redundancies and errors, then text quality is improved, but device complexity increases due to multiple processing algorithms
Solution Approach 1:
The patent implements a multi-functional text processing system where a single integrated platform performs multiple functions including redundancy detection, nonstandard expression identification, grammar checking, and style consistency verification, thereby achieving comprehensive text quality improvement without proportionally increasing system complexity through functional integration
Solution Approach 2:
The system merges natural language processing algorithms, machine learning models, and text analysis tools into a unified processing framework that works together to identify and correct various text issues simultaneously, reducing overall system complexity compared to using separate independent tools for each function
3Productivity
If automated text processing is implemented using machine learning algorithms, then productivity is improved, but measurement precision may worsen due to challenges in accurately detecting semantic similarity
Solution Approach 1:
The patent incorporates feedback mechanisms where the system learns from user corrections and validation inputs, continuously refining its similarity detection algorithms to improve measurement precision while maintaining high productivity through automated processing of text redundancies and nonstandard expressions
Data Source
AI summary
The present disclosure provides a computer-implemented method, computer system and computer program product for text processing. The present in invention may include obtaining an original text input from a collaborative development environment. The present invention may include extracting a first text statement from the original input text. The present invention may include calculating a similarity value between the first text statement and a second text statement, wherein the second text statement is obtained from a statement database. The present invention may include comparing the similarity value to a pre-set threshold.